projek visdat

library(jsonlite)
library(readxl)
library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(sf)

## Linking to GEOS 3.13.0, GDAL 3.10.1, PROJ 9.5.1; sf_use_s2() is TRUE

library(geojsonio)

## Registered S3 method overwritten by 'geojsonsf':
##   method        from   
##   print.geojson geojson

## 
## Attaching package: 'geojsonio'

## The following object is masked from 'package:base':
## 
##     pretty

library(writexl)

Input File json dan excel yang akan di-merged

# Baca file JSON
data_json = fromJSON("C:\\Users\\MUTHI'AH IFFA\\Downloads\\projek visdat\\Jabar_By_Kab.geojson")

# Baca file Excel (default: sheet pertama)
data_excel = read_excel("C:\\Users\\MUTHI'AH IFFA\\Downloads\\projek visdat\\SUSENAS2023.xlsx")

Konversi data json dan excel ke bentuk data frame

class(data_json)     

## [1] "list"

class(data_excel) 

## [1] "tbl_df"     "tbl"        "data.frame"

data_json = st_read("C:\\Users\\MUTHI'AH IFFA\\Downloads\\projek visdat\\Jabar_By_Kab.geojson") 

## Reading layer `Jabar_By_Kab' from data source 
##   `C:\Users\MUTHI'AH IFFA\Downloads\projek visdat\Jabar_By_Kab.geojson' 
##   using driver `GeoJSON'
## Simple feature collection with 27 features and 8 fields
## Geometry type: MULTIPOLYGON
## Dimension:     XY
## Bounding box:  xmin: 106.3705 ymin: -7.823398 xmax: 108.8338 ymax: -5.91377
## Geodetic CRS:  WGS 84

df = as.data.frame(data_json)
View(df)
str(data_json)

## Classes 'sf' and 'data.frame':   27 obs. of  9 variables:
##  $ OBJECTID  : int  1 2 3 4 5 6 7 8 9 10 ...
##  $ PROVINSI  : chr  "JAWA BARAT" "JAWA BARAT" "JAWA BARAT" "JAWA BARAT" ...
##  $ PROVNO    : chr  "32" "32" "32" "32" ...
##  $ KABKOTNO  : chr  "01" "02" "03" "04" ...
##  $ KABKOT    : chr  "BOGOR" "SUKABUMI" "CIANJUR" "BANDUNG" ...
##  $ ID_KAB    : num  3201 3202 3203 3204 3205 ...
##  $ Shape_Leng: num  4.45 4.05 4.89 3.09 3.48 ...
##  $ Shape_Area: num  0.245 0.34 0.294 0.144 0.253 ...
##  $ geometry  :sfc_MULTIPOLYGON of length 27; first list element: List of 1
##   ..$ :List of 3
##   .. ..$ : num [1:10876, 1:2] 107 107 107 107 107 ...
##   .. ..$ : num [1:4, 1:2] 107.13 107.13 107.13 107.13 -6.47 ...
##   .. ..$ : num [1:3501, 1:2] 107 107 107 107 107 ...
##   ..- attr(*, "class")= chr [1:3] "XY" "MULTIPOLYGON" "sfg"
##  - attr(*, "sf_column")= chr "geometry"
##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA NA
##   ..- attr(*, "names")= chr [1:8] "OBJECTID" "PROVINSI" "PROVNO" "KABKOTNO" ...

ubah kabkot no menjadi numeric

df = df %>% mutate(KABKOTNO = as.numeric(KABKOTNO))
View(df)

Merged data json dan excel

data_merged = left_join(df, data_excel, by = "KABKOTNO")

## Warning in left_join(df, data_excel, by = "KABKOTNO"): Detected an unexpected many-to-many relationship between `x` and `y`.
## ℹ Row 1 of `x` matches multiple rows in `y`.
## ℹ Row 32859 of `y` matches multiple rows in `x`.
## ℹ If a many-to-many relationship is expected, set `relationship =
##   "many-to-many"` to silence this warning.

View(data_merged)

Download dalam bentuk Json biasa

st_write(data_merged, “C:\Users\MUTHI’AH IFFA\Downloads\Jabar_By_Kab_baru.geojson”)

Download/konversi dalam bentuk .shp

data = st_read(“C:\Users\MUTHI’AH IFFA\Downloads\Jabar_By_Kab_baru.geojson”)

#konversi ke dalam .shp st_write(data, “C:\Users\MUTHI’AH IFFA\Downloads\Jabar_By_Kab_baru.geojson”)